New Configuration of the CO2 Capture Process Using Aqueous Monoethanolamine for Coal-Fired Power Plants

New Configuration of the CO2 Capture Process Using Aqueous Monoethanolamine for Coal-Fired Power Plants
이웅Jaeheum JungYeong Su JeongYoungsub LimChonghun Han
Issue Date
Industrial & engineering chemistry research
VOL 54, NO 15-3878
Postcombustion CO2 capture with aqueous monoethanolamine (MEA) scrubbing is one of the most promising and well-proven techniques for reducing CO2 emissions into the atmosphere. However, this process has a critical problem: the high reboiler heat energy requirement for solvent regeneration at the stripper reboiler. To reduce the reboiler heat requirement, this paper suggests a new stripper configuration for CO2 capture with MEA, namely a combined rich vapor recompression (RVR) and cold solvent split (CSS). The RVR is a newly developed configuration, involving vaporizing a cold solvent in the heat exchanger, thereby maximizing the heat exchanger preheating duty under low pressure. The CSS is a well-known configuration, feeding the split cold solvent to the stripper top and eliminating the reflux rate in the stripper by cooling the stripper top. The RVR process is dramatically improved when it is combined with the CSS configuration. To show the effect of this combined process, this study includes simulation of the Base process and of five alternative processes and also comparisons with reported data. A base model was established based on the operating data from a 0.1 MW pilot plant in South Korea. Consequently, the reboiler heat requirement in the combined the RVR and CSS process was reduced from 3.44 MJ(th)/kg CO2 to 2.75 MJ(th)/kg CO2. The total equivalent energy requirement for CO2 capture and the compression process was reduced from 1.224 MJ(e)/kg CO2 to 1.150 MJ(e)/kg CO2. This combined configuration reduced the total equivalent work by up to 6.0% compared with the conventional MEA process and was 1.7-3.4% lower than that of the lean vapor recompression (LVR) process, which is a well-known advanced MEA process.
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